regulatory-elements

Classify genomic regulatory elements from ENCODE chromatin signatures.

26|5|Updated Mar 8, 2026
One-click install
npx skills add https://github.com/ammawla/encode-toolkit --skill regulatory-elements
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: regulatory-elements
Source: https://github.com/ammawla/encode-toolkit/tree/main/plugin/skills/regulatory-elements
Command: npx skills add https://github.com/ammawla/encode-toolkit --skill regulatory-elements

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables users to discover, classify, and interpret genomic regulatory elements such as enhancers, promoters, silencers, and insulators, facilitating functional genome annotation.

Core Features & Use Cases

  • Regulatory Element Identification: Uses ENCODE data and chromatin signatures to find active and poised regulatory regions.
  • Classification by Chromatin State: Differentiates promoters, enhancers, insulators, and repressed regions based on histone marks and accessibility.
  • Application: For example, identify active enhancers in liver tissue from ENCODE datasets to assist in disease research or functional annotation.

Quick Start

Search for H3K27ac and H3K4me1 experiments in your tissue to classify enhancers and linked regulatory regions.

Frequently Asked Questions about regulatory-elements

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I classify genomic regulatory elements using chromatin state models?

Classifying genomic regulatory elements with chromatin state models requires ENCODE histone mark and accessibility data to distinguish enhancers, promoters, and silencers. This Skill analyzes chromatin signatures to identify active and poised regions for functional annotation.

What ENCODE data do I need to identify active enhancers in a specific tissue?

To identify active enhancers in a specific tissue, you need ENCODE histone mark and accessibility data, specifically H3K27ac and H3K4me1 experiments. This Skill analyzes these chromatin signatures to classify active and poised regulatory regions.

Can I use this approach to interpret non-coding variants in functional genomics studies?

Yes, you can interpret non-coding variants by classifying the regulatory elements where they reside. This Skill identifies whether variants fall within active enhancers, promoters, or insulators using chromatin state models and ENCODE data.

What is the difference between promoters and enhancers when analyzing histone marks?

The difference between promoters and enhancers lies in their chromatin signatures and histone mark combinations. This Skill differentiates promoters, enhancers, insulators, and repressed regions by analyzing ENCODE histone marks and accessibility peaks.

Are there limitations to classifying silencers and insulators with chromatin signatures?

Limitations in classifying silencers and insulators with chromatin signatures stem from the reliance on available ENCODE histone mark and accessibility data. Accurate peak analysis depends on the quality and coverage of the input chromatin state models.